Open Life Sci. 2015; 10: 19–29

1 Introduction

Genetic diversity of a species is defined as the sum of genetic

variability within a gene pool. Therefore, characterization

of natural species must include intra- and inter-

population genetic variability and the characteristics of

dynamic relations, such as gene flow, balancing selection

or mate limitation [1]. SSRs (simple sequence repeats or

microsatellites) have been widely used in plant genetic

research due to their high reproducibility, polymorphism,

co-dominant character and abundance in plant genomes

[2–5]. SSR markers have been isolated from European

pear [6–8] as well as from Asian pear species [9,10].

Additionally, a large number of SSRs isolated from apple

have revealed transferability to pear [11,12]. These markers

have been used for Pyrus genome mapping [7,12–15], as

well as for genetic resource characterization [16–21].

The pear (Pyrus spp.) genus is variously said to

consist of from 20 to over 70 wild or domesticated species

[22–25]. It is relatively difficult to give an accurate number

of pear species, because they easily cross-pollinate and

the obtained crosses have ambiguous taxonomic status.

The existence of a very large number of cultivars, species,

subspecies, hybrids and clones reinforces the need for

genetic characterization and verification. Wild pear (Pyrus

pyraster = P. commusis ssp. pyraster L.) is a woody plant

and closely related to the European pear (P. communis).

This species comes from the western Black Sea region and

the distribution of the species extends from the British

Isles to Latvia [26–29]. The wild pear is the only species of

pears that grows naturally in the region of Central Europe.

However, its taxonomic definitions appear inadequate

and conflicting because of the extensive morphological

heterogeneity of individual plants identified as P. pyraster

[27,28].

In Poland wild pear trees are widespread components

of human-made and natural habitats: mid-field shrub

communities, rural landscapes and forest ecosystems [30].

Wild pear shows high morphological heterogeneity, which

may have resulted from many centuries of growing in

proximity to pear orchards that prompted various stages of

Abstract: In order to provide molecular characteristics

of wild pear (P. pyraster) resources, six populations

(192 accessions) from different regions of Poland were

investigated with 17 SSR loci. Each of the SSR loci used

was polymorphic, with a mean of 19.5 alleles per locus

and a mean PIC of 0.806. Both the high heterozygosity (Ho

= 0.751) and low Fis (0.007) indicated that the wild pear

populations maintain a relatively high level of diversity,

while the mean F

index

of 0.039 and the number of migrants

per generation (Nm = 6.996) revealed a high gene flow and

weak inter-population differentiation. AMOVA analysis

located polymorphisms mainly within populations (96%).

Genetic relations between populations did not show

correlations with geographical distances. The dispersal

influence of gene flow could be the reason of the disrupted

relationship within populations and the low inter-

population differentiation. We did not find any evidence

to support the hypothesis about influence of interspecies

hybridization with pear cultivars on the level of wild pear

population diversity.

Keywords: microsatellite, SSR, Pyrus pyraster, wild pear,

genetic diversity, population structure

DOI 10.1515/biol-2015-0003
Received November 12, 2013; accepted May 11, 2014

Research Article

Open Access

© 2015 Łukasz Wolko, et al., licensee De Gruyter Open.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.

Łukasz Wolko*, Jan Bocianowski, Wojciech Antkowiak, Ryszard Słomski

Genetic diversity and population structure of wild

pear (Pyrus pyraster (L.) Burgsd.) in Poland

*Corresponding author: Łukasz Wolko: Department of Biochemistry

and Biotechnology, Poznan University of Life Sciences, 60-637

Poznan, Poland, E-mail: [e-mail]

Ryszard Słomski: Department of Biochemistry and Biotechnology,

Poznan University of Life Sciences, 60-637 Poznan, Poland

Jan Bocianowski: Department of Mathematical and Statistical

Methods, Poznan University of Life Sciences, 60-637 Poznan, Poland

Wojciech Antkowiak: Department of Botany, Poznan University of

Life Sciences, 60-625 Poznan, Poland

Ryszard Słomski: Institute of Human Genetics, Polish Academy of

Sciences, 60-493 Poznań, Poland

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20

 

 Ł. Wolko et al.

hybridization between native P. pyraster and P. communis

[31–34]. These hypothetical hybrids presenting various

traits typical of P. pyraster in combination with traits typical

of P. communis are classified as Pyrus ×amphigenea Domin

ex Dostálek [31]. Alternatively, the high morphological

heterogeneity of wild pear may be the effect of balancing

selection caused by a self-incompatibility mechanism.

Studies of polymorphism within the S-locus (genes that

limit compatibility of mating partners) have revealed high

variability even in small P. pyraster populations [35–38].

Developing genetic characterization of natural wild

pear populations should make a contribution to the

debate on potential effects on wild pear introgressive

hybridization and provide information concerning the

ecological condition of P. pyraster. Genetic characterization

of natural wild pear resources could be helpful in an

effective conservation effort of the species, which could

be applicable to exchange traits with cultivated varieties

in breeding programs. Therefore the aims of this study

were to assess the microsatellite loci polymorphism in the

P. pyraster species and to estimate the genetic variation on

the inter- and intra-population levels.

2 Experimental Procedures

2.1 Plant material sampling and DNA

extraction

Wild pear (P. pyraster) from six populations in northern

and central Poland were used in this study: the Bielinek

Reserve (BL), Biedrusko (BD), Brodnica (BR), Głuchów

(GL), Piotrków Trybunalski (PT) and Wyszków (WS)

(Table 1 and Figure 1). We limited number of samples

depending on population size. For small populations

samples were collected from all trees and from larger

populations around 30 samples were collected at random

from different locations of the populations. Overall, 192

trees were tested. The populations were not situated in

the immediate vicinity of horticultural centres; however

we could not exclude possibility of gen flow from pears

growing in rural gardens.

The young leaves collected were immediately placed

in plastic bags containing moist filter paper. Genomic

DNA was extracted from 2 g of fresh leaf material following

a modified cetyltrimethylammonium bromide (CTAB)

protocol [39].

2.2 PCR amplification and electrophoresis

A total of 17 SSR primer pairs were obtained from

Fernandez-Fernandez et al. [8] and Yamamoto et al. [6,10]

(Table 2). Microsatellite amplification was conducted

using 2 x PCR Master Mix (Fermentas Life Sciences,

Canada) [Components: Taq DNA polymerase 0.5 units/µl,

MgCl

2

4 mM and dNTP 0.4 mM]. 50 ng of genomic DNA

was mixed with 10 ng of each primer (the forward primer

labeled with a fluorescent chemical FAM, TET or HEX),

1 x PCR Master Mix and distilled water to make up the

final volume of 20 µl. Amplification was performed with

35 cycles at 94°C for 1  min, 42–55°C for 1 min and 72°C

for 2 minutes, for denaturation, annealing and primer

extension, respectively. The PCR products were separated

and detected using a MegaBACE 1000 (GE Healthcare

Table 1: Characteristics of six wild pear populations.

Abbr – Abbreviation; Cs – approximate census size; Ss – sample size; Gp – geographical parameters.

Abbr

Cs/Ss

Gp

Population characteristics

BL

150/36

14°08’ E

52°56’ N

Large natural population of moderate density; it originated from natural colonization by wild pear

trees of xerothermic grasslands, the driest and sunniest slopes of the Bielinek reserve.

BD

1500/30

16°55’ E

52°33’ N

The largest population of P. pyraster in Poland located in the Biedrusko army training ground, esta-

blished in the early 20th century and it has been in use by the Polish military since then. The wild

pear population has probably grown there since the end of agricultural usage; the large population

consists of dispersed trees and small groups of trees growing close together.

BR

29/29

19°23’ E

53°19’ N

Medium-sized population; trees growing near dirt roads within several meters of each other.

GL

50/30

20°04’ E

51°46’ N

Medium-sized population; trees scattered along agricultural fields, growing several hundred meters

from each other.

PT

50/32

19°39’ E

51°27’ N

Medium-sized population; trees scattered along agricultural fields, growing several hundred meters

from each other.

WS

50/35

21°27’ E

52°35’ N

Medium-sized population; trees scattered along agricultural fields, growing a at a distance of 100

- 200 m from each other.

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Life Sciences, USA) sequencer. The size of the amplified

bands was determined based on internal standard DNA

(MegaBACE ET550-R Size Standard) with the MegaBACE

Fragment Profiler Version 1.2 (GE Healthcare).

2.3 Data analysis

We estimated the genetic information for 17 SSR loci in

six P. pyraster populations: the number of individual

alleles (N), frequency of the most prevalent allele (p),

number of private alleles unique to a single population

(Np), inbreeding coefficient for an individual relative to

the subpopulation (Fis), fixation index (F

index

) and the

number of migrants per generation (Nm). [40,41]. The

fixation index is a measure of population differentiation

due to genetic structure. It is frequently estimated from

genetic polymorphism data. Developed as a special case

of Wright’s F-statistics, it is one of the most commonly

used statistics in population genetics. This comparison

of genetic variability within and between populations is

frequently used in applied population genetics. The values

range from 0 to 1. A zero value implies complete panmixis;

that is, that the two populations are interbreeding

freely. A value of one implies that all genetic variation is

explained by the population structure, and that the two

populations do not share any genetic diversity. Variability

for each locus was measured using the polymorphism

information content (PIC) [42]

,

1

2

∑

−

=

n

i

i

p

PIC

where pi is the frequency of the ith allele (Table 3).

The following analyses were performed using the

GenAlEx version 6.41: the number of different alleles across

20 SSR loci in populations (Na), the number of private

alleles unique to a single population (Np), the percentage

of private alleles (Np%), Shannon’s information index (I),

observed heterozygosity (Ho), expected heterozygosity

(He), and inbreeding coefficient (Fis) [43]. Shannon’s

information index is an index of biodiversity. Tests for

Figure 1: Distribution of the six studied populations across Poland (for population abbreviation see 2.1).

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 Ł. Wolko et al.

deviations from the Hardy-Weinberg equilibrium (HWE)

according to Falconer and Mackay [44] and possible

deviations of genotype frequencies from their expected

values were analyzed using the chi-square test (c

2

).

The analysis of molecular variance (AMOVA) was

used to compute the distribution of genetic variability

among and within populations. The GenAlEx version 6.41

allows for the calculation of AMOVA. Significance levels

for estimated variance components were computed using

1000 permutations [45]. The data for microsatellite allele

frequency were applied to calculate the unbiased genetic

distance and genetic identity estimates by employing

Nei’s genetic distance [46]. Pairwise, genetic distances

between individuals as well as between populations were

Table 2: Characteristics of 17 microsatellite primer pairs including SSR repeat motif. 1-9 Fernandez-Fernandez et al. 2006 [8]; 11- Yamamoto

et al. 2002 ; 12-17 Yamamoto et al. 2002 [10].

No.

Marker

Repeat motif

Primer sequences (5′−3′)

Size range (bp) Most prevalent allele (bp)

1.

EMPc10

AC

F: TTAAGCAAGTGGGCAAGTAGG

R: TTCCGTATCGCTTGTGTCTAC

150-196

160

2.

EMPc102

CT

F: CGATGATCCATCATTAAGTCCC

R: TCAAGTTCTGCTTCATTTCCAG

142-193

178

3.

EMPc105

AG

F: TCAAGATGGACCAAAAAGGTTC

R: AGAGGTGCAAAGATATTCCAGG

122-198

180

4.

EMPc106

AG

F: CGATTCAAATCAGCCTATTCTGT

R: CACTTATCGACATCTGTCAGCC

104-224

204

5.

EMPc110

CT

F: ACTAACATTAAAAAATCTTTAC

R: ATCTTAAAACTTAAACTAAATAA

96-150

160

6.

EMPc111

AG

F: CAAACCTTCCAACCTCAACAAT

R: CCGATCAGAAAGAGCTGTGAGT

82-122

100

7.

EMPc114

AG

F: ACCCACAATTCCCCATAT

R: AGCCTTATGCGCCTTCTA

132-186

139

8.

EMPc115

GT

F: AGAAGCGAGGAAGCAGTGTAT

R: CATGTAGACCAGTTTCATTTGC

161-196

183

9.

EMPc117

CT

F: GTTCTATCTACCAAGCCACGCT

R: CGTTTGTGTGTTTTACGTGTTG

92-138

103

10.

KA14

(CA)G(AC)G(CA) F: TCATTGTAGCATTTTTATTTTT

R: ATGGCAAGGGAGATTATTAG

171-199

187

11.

BGT23b

TC

F: CACATTCAAAGATTAAGAT

R: ACTCAGCCTTTTTTTCCCAC

164-239

210

12.

NB109a

AG

F: ATGCTCTATAAAACCCACCTACC

R: AGAGGGACCATTGTGTTATTGTAT

135-194

160

13.

NB113a

AG

F: ATGAAATATGTCGTGTTGCCCTTAG

R: CCCTTCCTCAGCATGTTTCCTAGAC

135-167

155

14.

NH025a

AG

F: CTGGACACAAACATTCAAGAGGG

R: CACACCAGAAACTCCAAAACAGG

50-106

70

15.

NH026a

AG

F: CGTAATACTCGTAGTGCATGATG

R:GCTTCTGGACTATCACTATTTCTTC

123-158

139

16.

NH027a

AG

F: TAATGTGTTGGGGAGAGAGAG

R: GCTCTTGTTCCTTGCTCCTAA

112-172

131

17.

NB141b

AG

F: TTCCTCCACTTGAGGGACAC

R: GTTGAAGGCATCGGATTGAT

82-121

93

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estimated using the proportion of shared allele approach

[47]. On the basis of calculated coefficients, individuals

as well as populations were grouped hierarchically, using

the unweighted pair group method of arithmetic means

(UPGMA). The relationships between individuals as well

as among populations were presented in the form of

dendrograms (Figures 2 and 3). Genetic differentiation

between pairs of populations across all loci was analyzed

based on estimates of t

st

values and N

m

.

The longitude and latitude coordinates were used

to construct the geographical distance matrix between

the studied populations. A Mantel test was computed

between genetic and geographical distances. In addition,

we used the Bayesian clustering method to elucidate the

genetic structure among populations of wild pear, and

to infer the most appropriate number of subpopulations

(K). Simulations were run 10 times with 200000 Markov

chain Monte Carlo sampling runs after a burn-in period

of 1000000 iterations, using the admixture model under

the assumption of correlated allele frequencies. The most

appropriate cluster number (K) was selected using the

criterion of [48].

3 Results

3.1 Characteristic of SSR markers and

genetic diversity

The transferability of SSR markers from P. communis

to P. pyraster has previously been tested [18]. Based on

these results, we selected the 17 SSR markers for the wild

pear natural population diversity analysis due to high

polymorphism (Table 2). Each of the 17 loci analysed

was polymorphic and a total of 332 putative alleles were

obtained, which gave a mean value of 19.5 alleles per locus.

Of the 17 microsatellite loci, only one (EMPc105) deviated

from the Hardy-Weinberg equilibrium (P = 0.023), due to

heterozygote deficiency.

The highest number of the alleles per locus were

obtained for EMPc106 (N = 35) and the lowest were for

NB113a (N = 11) (Table 3). The discrimination power of SSR

markers was described by: the polymorphism information

content (PIC), Shannon’s information index (I) and the

frequency of the most prevalent allele (p) (Table 3).

The highest discrimination power (PIC > 0.9, I > 2.3 and

Table 3: Genetic information for 17 SSR loci in six P. pyraster populations: N – number of alleles; Np – number of private alleles unique to a

single population; p – frequency of the most prevalent allele; I – Shannon’s information index; Fis – inbreeding coefficient for an individual

relative to the subpopulation; F

index

– Fixation index, Nm - number of migrants per generation; PIC – polymorphism information content.

Locus

N

Np

p

I

Fis

F

index

Nm

PIC

EMPc10

12

3

0.456

1.407

-0.108

0.038

6.341

0.695

EMPc102

21

5

0.391

2.000

0.022

0.040

6.018

0.811

EMPc105

24

7

0.177

2.386

0.266

0.046

5.194

0.916

EMPc106

35

10

0.297

2.303

0.001

0.042

5.721

0.876

EMPc110

18

3

0.719

1.114

0.059

0.031

7.715

0.474

EMPc111

15

2

0.357

1.738

-0.163

0.078

2.961

0.791

EMPc114

21

1

0.234

2.256

0.148

0.038

6.404

0.887

EMPc115

14

1

0.604

1.624

-0.014

0.017

14.055

0.730

EMPc117

21

3

0.151

2.362

0.075

0.039

6.178

0.911

KA14

12

2

0.495

1.458

-0.151

0.026

9.272

0.700

BGT23b

23

9

0.341

2.026

0.111

0.036

6.675

0.830

NB109a

28

5

0.229

2.427

-0.021

0.030

8.026

0.902

NB113a

11

4

0.492

1.452

-0.190

0.029

8.322

0.698

NH025a

21

3

0.169

2.368

0.027

0.048

4.926

0.918

NH026

15

0

0.279

2.224

-0.006

0.033

7.277

0.882

NH027a

25

4

0.179

2.329

0.216

0.036

6.661

0.907

NB141b

16

5

0.383

1.750

0.038

0.051

4.612

0.788

Mean

19.5

3.9

0.350

1.954

0.018

0.039

6.845

0.806

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Figure 2: Dendrogram of relationships among 192 wild pear trees based on UPGMA method according the data of SSR analysis

Figure 3: Dendrogram of genetic differentiation between six wild pear populations. The dendrogram based on Nei’s unbiased genetic dis-

tance using the UPGMA method, according to data from all SSR loci.

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25

p < 0.2) was estimated in the case of four loci: EMPc 105,

EMPc117, NH025a and NH027a. The lowest discrimination

power parameters were obtained for EMPc110 (PIC = 0.47,

I = 1.1, p = 0.72). The Fis mean value calculated for all SSR

loci was 0.018. Fis was highest for EMPc105 (Fis = 0.266)

and the lowest for NB113a (Fis = -0.19) (Table 3).

Private alleles unique to a single wild pear population

(Np) measure the genetic distinctiveness of the marker

for the tested populations and are useful for estimating

migration rates. The genetic diversity of the markers

does not demonstrate any correlation with the Np value.

The highest number of such alleles (10) was found for

the EMPc106, while no unique allele was detected for the

NH026 (Table 3).

3.2 Population variation

A mean of 11.75 alleles per population per locus were

detected. The BR with the highest number of alleles across

loci (mean Na = 12.52) and the BD with the highest number

of private alleles (Np = 17) seem to offer the most diversified

populations. The lowest number of alleles was observed

for the BL population (Na = 10.76) and the lowest number

of private alleles was recorded in BR (Np = 8) (Table 4).

The low mean value of fixation index (F

index

= 0.039)

indicated negligible population genetic differentiation

and low genetic divergence within the populations.

The number of migrants per generation (Nm) for loci

ranged between 2.961 and 14.274 with an average value of

6.845 (Table 3).

The high level of intra-population genetic diversity

was supported by the results for the Shannon information

index (mean value I = 1.954), as well as high observed and

expected heterozygosity (mean Ho = 0.751 and He = 0.762)

(Table 4). The population-wise inbreeding coefficient

(Fis) values were around zero (from -0.035 to 0.041) with

an average value of 0.018. This result suggested random

mating, no population subdivisions and a state close to

the Hardy-Weinberg equilibrium (Table 4).

Significant differentiation (F = 3.451; P  <  0.001)

among the six populations was further supported by the

results from analysis of molecular variance (AMOVA)

using microsatellites, where both the intra- and the inter-

population variability were found to be highly significant,

with 4.0% of the genetic variance attributed to the

differentiation among the six populations, whereas 96.0%

was the result of intra- population variability (Table 5).

The analysis of genetic differentiation between pairs

of populations confirms that differentiation was modest

(Table 6). The value of population differentiation (t

st

) was

the highest between PT and BD (0.033) and the lowest

between the BD and BR (0.016). The gene flow (N

m

) was the

highest between PT and WS (15.491) and lowest between

PT and BD (7.425) (Table 6).

Table 5: Summary of analysis of molecular variance (AMOVA) of microsatellite loci for comparison among and within all six populations. df

– degree of freedom (ratio statistic Rst = 0.037, P ≤ 0.01). Probability of obtaining a large component estimate; number of permutations =

1000.

Source of variation

Df

Sum of squares

Mean squares

Estimated variance

Percentage of variation

Among Pops

5

43456.618

8691.324

96.577

4

Within Pops

378

952118.048

2518.831

2518.831

96

Total

383

995574.667

2615.408

100

Table 4: Genetic diversity of wild pear populations. N – total number of alleles; Na – average number of different alleles per locus; Np –

number of private alleles unique to single population; Ne – number of effective alleles; I – Shannon’s information index; Ho – observed

heterozygosity; He – expected heterozygosity; Fis – inbreeding coefficient.

Population

N

Na

Np

Ne

I

Ho

He

Fis

BL

183

10.76

9

5.247

1.780

0.724

0.731

0.008

BD

207

12.17

17

6.245

1.984

0.763

0.781

0.013

BR

213

12.52

8

6.634

1.997

0.745

0.781

0.035

GL

196

11.53

11

5.194

1.891

0.735

0.771

0.041

PT

204

12.00

15

5.235

1.860

0.764

0.750

-0.029

WS

195

11.47

11

5.377

1.865

0.774

0.757

-0.035

Mean

199.7

11.75

11.8

5.655

1.954

0.751

0.762

0.018

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3.3 Genetic distances among individuals

and populations

UPGMA cluster analyses were conducted for single trees as

well as the six populations. The phylogenetic tree of single

individuals (Figure 2) shows a weak correlation between

the source population and genetic relationships inferred

from polymorphism of SSR loci. The pear trees could

be classified into six main groups, but all of the groups

consist of individuals from at least two populations. The

phylogenetic analysis of relationships between individual

trees may confirm the potential gene flow.

Nei’s unbiased genetic distance and identity were

estimated for each pair of populations (supplementary

materials). The distances ranged between 0.11 (PT – WS)

and 0.249 (PT – BD), while identity varied between 0.779

(BD – GL and PT – BD) and 0.896 (PT – WS). To elucidate

the relationships between populations, a dendrogram

was constructed on the basis of genetic distances

(Figure 3). Estimation of correlation coefficients between

genetic and geographical distances did not show any

correlation of these parameters (r = 0.0241, P = 0.9320).

Bayesian clustering analysis indicated the same grouping

as UPGMA cluster analyses.

4 Discussion

4.1 Characteristics and diversity of SSR

markers

The SSR markers used in the study demonstrated a high

degree of polymorphism. In total, the 17 SSR markers

allowed identification of 332 alleles in the 192 examined

P. pyraster genotypes. The resultant mean of 19.5 alleles

per locus (Table 3) was higher than the 14.8 reported

previously for wild pear by Kimura et al. [9], 17.3 by Volk

et al. [16] and 13 by Yakovin et al. [19]. The differences may

be a result of the loci examined and the large number of

individuals for geographically remote populations.

The length of the fragments obtained for the SSR loci

was described previously for P. communis [8,17,19,37];

however, allele lengths obtained for P. communis and

P. pyraster were often different [8,17] (Table 2). The most

often observed alleles were mostly (10 markers) of the

same length as previously described for P. communis [18].

4.2 Population variation

A heterozygosity level was recorded in the examined

populations proving their high genetic variation (mean

Ho=0.75). Similar ranges of Ho and He values have been

described for P. communis [8,17–19]. The differences in values

of Ho and He did not exceed 0.04 per population and were

generally not different in a statistically significant manner

(Table 4). Similar values of He and Ho, as well as a very low

mean inbreeding coefficient (Fis = 0.018) indicated that

the examined populations were near the Hardy-Weinberg

equilibrium state (Tables 3 and 4). This could be the effect

of a gametophytic self-incompatibility mechanism, which

prevents inbreeding in pear species [35–38].

Populations BD and BR seemed to be genetically

diversified to the highest degree because of the highest

values of alleles per locus (Na), effective alleles (Ne)

and Shannon’s information index (I) (Table 5). However,

the BR population had the lowest number of private

alleles (Np = 8) and the highest inbreeding coefficient

(Fis = 0.035), which could be the result of the small

size of this population. The population of BL showed

the weakest separation and genetic differentiation.

It is interesting that only this population was reported in

the wildlife reserve and this protection excluded human

interference, so this should have accelerated the natural

process of plant succession [30]. Two of the six studied

populations, BL and BD, could be described as natural

populations, whereas the BR, GL, PT and WS populations

Table 6: Analysis of genetic differentiation between pairs of populations across all loci based on estimates of t

st

values (below diagonal) and

N

m

(above diagonal). t

st

and N

m

values were negatively significantly correlated (r = -0.9641, p < 0.00001).

Populations

BL

BD

BR

GL

PT

WS

BL

***

9.852

9.997

7.894

10.055

11.573

BD

0.025

***

14.938

10.098

7.425

9.169

BR

0.024

0.016

***

10.622

8.166

10.490

GL

0.031

0.024

0.023

***

9.090

10.172

PT

0.024

0.033

0.030

0.027

***

15.491

WS

0.021

0.027

0.023

0.024

0.016

***

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Genetic diversity and population structure of wild pear (Pyrus pyraster (L.) Burgsd.) in Poland 

 

27

had anthropogenic sources. We conclude that our study

did not show significant differences in the level of

genetic variation between natural and human-created

populations.

Analysis of genetic distances and differentiation proved

that the highest genetic similarity was observed between two

pairs of populations: the PT – WS and BD – BR populations

(Tables 6). However, the genetic relations illustrated on

the dendrogram (Figure 3) did not show correlations with

geographical distances between populations (Figure 1).

The weak correlation between genetic and geographical

distances is difficult to explain. We could suspect an

accidental human impact during the process of plantation

of wild pear trees along mid-field and rural roads, but the

strength of this impact seems to be difficult to assess.

4.3 Population gene flow

Our study demonstrates that the high level of gene flow

appeared to be one of the most important elements

determining the genetic structure of wild pear populations.

Gene flow causes restriction of divergence between

populations, whereas genetic drift and directional selection

induce intra-population diversity [49,50]. In the case of

trees, gene flow is the result of pollen and seed spreading.

Long lifetime of trees may cause formation of multi-

generation populations when the gene flow and panmix

change the family structure and reduce inbreeding [49].

In the presented study the mean value of Fis was

below 0.05, which proved no population subdivision

and a lack of barriers in mutual pollination, while the

high level of gene flow and genetic homogeneity across

the examined populations were supported by F

index

and

Nm values (Table  3). The results of AMOVA localized

majority variation on the intra-population level (Table 5)

and the analysis of genetic differentiation between pairs

of populations also demonstrated a low inter-population

differentiation and high gene flow (Table 6).

The results allow us to conclude that the wild pear

species in Poland maintains a relatively high level of

genetic diversity. The high heterogeneity of the examined

populations may be the effect of pollination by insects or

seed spreading by animals [51–54], but the influence of

human activities could be suspected as well. The process

of genetic pool mixing via gene flow may have resulted

in relatively low relationships among the individuals

in multi-generation habitats, which is illustrated on the

dendrogram of individual accession (Figure 2). However,

further studies of the spatial population genetic structure

need to be conducted in order to characterize these

phenomena in detail.

Regular crossbreeding with cultivated pear varieties

could have led to inter-species hybridization and a decline

in natural characters of P. pytaster [31–34]. Meanwhile,

gametophytic type self-incompatibility, regulating

pollination in Pyrus should induce pressure on genetic

variability maintenance [16,18,34,37]. The strong influence

of gene flow from cultivations to the natural wild pear

populations should lead to genetic unification of the wild

population. Meanwhile, in a large study, populations

were detected with genetic diversity and gene flow, which

may give evidence against the influence of interspecific

hybridization

Acknowledgements: This study was funded from

resources allocated to research from 2009 to 2013, as

research project No. N N304 141337

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